Genetic algorithm fine tuning of Support Vector Data Descriptor (SVDD) for classification of monocotyledon and dicotyledon weeds

Wong, Wei Kitt and Muralindran Mariappan and Chekima Ali and Khoo, Brendan and Manimehala Nadarajan (2014) Genetic algorithm fine tuning of Support Vector Data Descriptor (SVDD) for classification of monocotyledon and dicotyledon weeds. International Journal of Enhanced Research in Science Technology & Engineering, 3 (8). pp. 201-205. ISSN 2319-7463

[img]
Preview
Text
Genetic algorithm fine tuning of Support Vector Data Descriptor.pdf

Download (45kB) | Preview

Abstract

Weed recognition using image processing has been performed and improved in various papers. In this paper, weed seedlings were discriminated using Support Vector Data Descriptor (SVDD) to identify monocotyledon weeds from mixture of monocotyledon and dicotyledon weeds. The feature selection and parameter fine tuning were performed using genetic Algorithm (GA). The resulting SVDD configurations were tested using 200 image samples. The best configurations gave an average of 95% recognition rate.

Item Type: Article
Keyword: Support Vector Data Descriptor (SVDD), Genetic Algorithm (GA)
Subjects: Q Science > QK Botany
Department: FACULTY > Faculty of Engineering
Depositing User: MUNIRA BINTI MARASAN -
Date Deposited: 20 Jun 2018 08:23
Last Modified: 20 Jun 2018 08:23
URI: https://eprints.ums.edu.my/id/eprint/20215

Actions (login required)

View Item View Item